crewAI Banking Automation

Multi-agent AI automation workflows for Alpine Capital Bank operations - continuously improving

Production-ready automation projects using the crewAI framework to orchestrate autonomous AI agents across banking and financial services operations.

Overview

This repository contains 23 specialized automation projects designed for Alpine Capital Bank, organized across four departments:

• Human Resources (10 projects): Recruitment, training, employer branding, social media
• Operations (5 projects): Customer engagement, VIP services, financial analysis
• Information Technology (4 projects): Documentation, policy validation, landing pages
• Flows (3 projects): Advanced orchestration with email, leads, and meetings

Each project leverages multi-agent collaboration where specialized AI agents work together autonomously to complete complex, multi-step tasks.

Key Features

• Banking-Focused Context: All agents operate within Alpine Capital Bank environment with appropriate financial services terminology
• Production-Ready: Python packages with YAML configuration, dependency management, and testing support
• Dual Architecture: Educational Jupyter notebooks + enterprise Python packages
• Advanced Orchestration: Flow-based state management for continuous background operations
• Compliance-Aware: Designed for banking regulatory requirements and audit trails

Quick Start

Prerequisites

• Python 3.10-3.13
• UV or Poetry package manager
• OpenAI API key (or compatible LLM endpoint)

Installation

# Clone repository
git clone https://github.com/GitSolved/crewAI-Banking-Automation.git
cd crewAI-Banking-Automation

# Install UV (recommended)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Navigate to a project
cd Alpine/Human-Resources-Department/Banking_Recruitment_Automation

# Install dependencies
uv sync

# Configure environment
cp .env.example .env
# Edit .env with your API keys

# Run the automation
uv run recruitment

Projects by Department

Human Resources Department

| Project | Type | Description | |---------|------|-------------| | Banking_Recruitment_Automation | Python Package | Multi-agent recruitment workflow with LinkedIn integration and candidate profiling | | Job_Posting_Generator | Python Package | Automated banking job posting creation optimized for financial roles | | Resume_Job_Matcher | Python Package | AI-powered candidate-role matching with scoring system | | Employer_Branding_Automation | Python Package | Strategic employer branding and talent marketing campaign development | | Professional_Social_Media_Content | Standalone Python | Tactical social media content for LinkedIn/Twitter banking communications | | Meeting_Preparation_Assistant | Standalone Python | Meeting prep, agenda creation, and briefing materials | | Corporate_Travel_Planner | Standalone Python | Employee travel coordination and itinerary generation | | Training_Video_Script_Generator | Standalone Python | Employee training content and script generation | | Event_Planning_Automation | Jupyter Notebook | Banking events, conferences, and corporate retreat planning | | Job_Application_Booster | Jupyter Notebook | Resume screening with structured evaluation and scorecards |

Operations Department

| Project | Type | Description | |---------|------|-------------| | VIP_Client_Experience_Planner | Python Package | High-net-worth client experience design and luxury event planning | | Stock_Analysis_Automation | Python Package | Advanced financial analysis and trading strategy development | | Customer_Outreach_Campaign | Jupyter Notebook | Customer engagement campaigns with segment-specific messaging | | Customer_Support_Automation | Jupyter Notebook | Automated support ticket handling and response generation | | Financial_Analysis | Jupyter Notebook | Stock analysis with hierarchical agent collaboration |

Information Technology Department

| Project | Type | Description | |---------|------|-------------| | Policy_Document_Validator | Python Package | Compliance policy validation for markdown format documents | | Landing_Page_Generator | Python Package | Marketing page generation and A/B testing optimization | | Article_Automation | Jupyter Notebook | Internal documentation and knowledge base article generation |

Alpine Flows

Advanced orchestration using crewAI Flows for state management and continuous operation:

| Flow | Description | |------|-------------| | Email_Auto_Responder_Flow | Automated email checking and draft response generation (Gmail API) | | Lead_Score_Flow | Lead qualification, scoring, and automated follow-up | | Meeting_Assistant_Flow | Meeting coordination and automated follow-up tasks |

Architecture

Project Types

Python Packages (17 projects):

• YAML-based agent/task configuration
• Production-ready with pyproject.toml
• Dependency management via UV/Poetry
• Enterprise-scale deployment ready

Standalone Python (3 projects):

• Self-contained scripts with requirements.txt
• Agents and tasks defined in separate .py files
• Suitable for rapid prototyping

Jupyter Notebooks (3 projects):

• Educational and exploratory workflows
• Inline code with markdown documentation
• Great for learning crewAI patterns

Flow Packages (3 projects):

• Event-driven architecture with state management
• Background workers for continuous operation
• Advanced multi-crew orchestration

Running Projects

Python Packages

cd Alpine/<Department>/<Package-Name>
uv sync                    # Install dependencies
uv run <package-name>      # Run automation
uv run train 5             # Train mode (if supported)

Standalone Python

cd Alpine/<Department>/<Project-Name>
pip install -r requirements.txt
python main.py

Jupyter Notebooks

cd Alpine/<Department>/<Project-Name>
pip install -r requirements.txt
jupyter notebook <notebook-file>.ipynb

Flow Packages

cd Alpine-Flows/<Flow-Name>
uv sync
# Add credentials.json if required (e.g., Gmail API)
uv run kickoff  # Runs continuously in background

Configuration

All projects require environment variables:

# Create .env file in project root
OPENAI_API_KEY=your-key-here
OPENAI_MODEL_NAME=gpt-4-turbo  # or gpt-3.5-turbo
SERPER_API_KEY=your-key-here   # For web search tools

Project-Specific Requirements:

• Banking_Recruitment_Automation: LinkedIn cookie (LI_AT)
• Email_Auto_Responder_Flow: Gmail API credentials.json
• Resume_Job_Matcher: Vector database setup

Documentation

• CLAUDE.md: Comprehensive development guide with architecture details, project structures, and development workflows
• CREWAI_TUTORIAL.md: Complete crewAI framework tutorial with examples and best practices
• Project READMEs: Each project has its own README with specific setup and usage instructions

Example Use Cases

Recruitment Automation

cd Alpine/Human-Resources-Department/Banking_Recruitment_Automation
uv run recruitment
# Input: Job position and LinkedIn search criteria
# Output: Candidate profiles, interview materials, coordination plans

VIP Client Experience

cd Alpine/Operations-Department/VIP_Client_Experience_Planner
uv run surprise_trip
# Input: Client preferences, destination, dates
# Output: Luxury itinerary with Michelin dining, exclusive activities

Employer Branding Campaign

cd Alpine/Human-Resources-Department/Employer_Branding_Automation
uv run employer_branding
# Input: Company values, target talent demographics
# Output: Strategic branding campaign with positioning framework

Development

Adding Custom Tools

# src/<package>/tools/my_tool.py
from crewai_tools import BaseTool

class BankingAnalysisTool(BaseTool):
    name: str = "Banking Analysis Tool"
    description: str = "Analyzes banking data"

    def _run(self, data: str) -> str:
        # Implementation
        return result

Modifying Agent Configuration

# src/<package>/config/agents.yaml
financial_analyst:
  role: "Senior Financial Analyst"
  goal: "Provide accurate financial insights for Alpine Capital Bank"
  backstory: "FINRA-approved analyst with 15 years in banking"
  tools:
    - serper_tool
    - banking_analysis_tool

Technology Stack

• Framework: crewAI - Multi-agent orchestration
• LLM: OpenAI GPT-4 / GPT-3.5 (configurable)
• Tools: SerperDev (search), custom banking tools
• Package Management: UV, Poetry
• Notebooks: Jupyter
• Version Control: Git

Repository Structure

crewAI-Banking-Automation/
├── Alpine/
│   ├── Human-Resources-Department/     # 10 HR automation projects
│   ├── Operations-Department/          # 5 operations projects
│   └── Information-Technology-Department/  # 4 IT projects
├── Alpine-Flows/                       # 3 flow-based orchestrations
├── CLAUDE.md                           # Comprehensive development guide
├── CREWAI_TUTORIAL.md                  # Framework tutorial
└── README.md                           # This file

Best Practices

1. Start with notebooks for learning crewAI patterns
2. Use Python packages for production deployments
3. Review CLAUDE.md for architecture decisions
4. Set verbose=True during development for debugging
5. Enable memory (memory=True) for context retention
6. Use hierarchical mode for complex multi-step tasks

License

MIT License - See individual project directories for specific licensing.

Contributing

1. Fork the repository
2. Create a feature branch
3. Follow existing project structure patterns
4. Ensure all agents reference Alpine Capital Bank
5. Test with verbose=True mode
6. Submit pull request

Resources

• crewAI Documentation
• crewAI GitHub
• OpenAI API Documentation
• CLAUDE.md - Repository-specific development guide
• CREWAI_TUTORIAL.md - Framework tutorial

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Alpine Capital Bank - Transforming banking operations through intelligent automation